A Low Complexity Euclidean Norm Approximation

Autor:	Kyungwhoon Cheun, Changkyu Seol
Rok vydání:	2008
Předmět:	Discrete mathematics Euclidean distance Unit vector Norm (mathematics) Signal Processing Vector quantization Matrix norm Applied mathematics Electrical and Electronic Engineering Linear combination Mathematics Normed vector space Euclidean vector
Zdroj:	IEEE Transactions on Signal Processing. 56:1721-1726
ISSN:	1941-0476 1053-587X
DOI:	10.1109/tsp.2007.909354
Popis:	The need for real-time computation of the Euclidean norm of a vector arises frequently in many signal processing applications such as vector median filtering, vector quantization and multiple-input multiple-output wireless communication systems. In this correspondence, we examine the properties of a linear combination of the 1-norm and the infinity norm as an approximation to the Euclidean norm of real-valued vectors. The approximation requires only two multiplications regardless of the vector length and does not require sorting of the absolute values of the vector entries. Numerical results show that the considered approximation incurs negligible performance degradations in typical applications.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::7012e28ba1bd523d1aa9c8a6774cae4c https://doi.org/10.1109/tsp.2007.909354 Zobrazit plný text záznamu